{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Ridge Regression"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-09-19T12:11:53.493495Z",
     "start_time": "2023-09-19T12:11:53.345854Z"
    }
   },
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "\n",
    "from sklearn.linear_model import LinearRegression\n",
    "from sklearn.linear_model import Ridge\n",
    "from sklearn.preprocessing import StandardScaler\n",
    "\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-09-19T12:11:53.526279Z",
     "start_time": "2023-09-19T12:11:53.492248Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(400, 11)\n"
     ]
    },
    {
     "data": {
      "text/plain": "    Income  Limit  Rating  Cards  Age  Education  Gender Student Married  \\\n1   14.891   3606     283      2   34         11    Male      No     Yes   \n2  106.025   6645     483      3   82         15  Female     Yes     Yes   \n3  104.593   7075     514      4   71         11    Male      No      No   \n4  148.924   9504     681      3   36         11  Female      No      No   \n5   55.882   4897     357      2   68         16    Male      No     Yes   \n\n   Ethnicity  Balance  \n1  Caucasian      333  \n2      Asian      903  \n3      Asian      580  \n4      Asian      964  \n5  Caucasian      331  ",
      "text/html": "<div>\n<style scoped>\n    .dataframe tbody tr th:only-of-type {\n        vertical-align: middle;\n    }\n\n    .dataframe tbody tr th {\n        vertical-align: top;\n    }\n\n    .dataframe thead th {\n        text-align: right;\n    }\n</style>\n<table border=\"1\" class=\"dataframe\">\n  <thead>\n    <tr style=\"text-align: right;\">\n      <th></th>\n      <th>Income</th>\n      <th>Limit</th>\n      <th>Rating</th>\n      <th>Cards</th>\n      <th>Age</th>\n      <th>Education</th>\n      <th>Gender</th>\n      <th>Student</th>\n      <th>Married</th>\n      <th>Ethnicity</th>\n      <th>Balance</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>1</th>\n      <td>14.891</td>\n      <td>3606</td>\n      <td>283</td>\n      <td>2</td>\n      <td>34</td>\n      <td>11</td>\n      <td>Male</td>\n      <td>No</td>\n      <td>Yes</td>\n      <td>Caucasian</td>\n      <td>333</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>106.025</td>\n      <td>6645</td>\n      <td>483</td>\n      <td>3</td>\n      <td>82</td>\n      <td>15</td>\n      <td>Female</td>\n      <td>Yes</td>\n      <td>Yes</td>\n      <td>Asian</td>\n      <td>903</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>104.593</td>\n      <td>7075</td>\n      <td>514</td>\n      <td>4</td>\n      <td>71</td>\n      <td>11</td>\n      <td>Male</td>\n      <td>No</td>\n      <td>No</td>\n      <td>Asian</td>\n      <td>580</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>148.924</td>\n      <td>9504</td>\n      <td>681</td>\n      <td>3</td>\n      <td>36</td>\n      <td>11</td>\n      <td>Female</td>\n      <td>No</td>\n      <td>No</td>\n      <td>Asian</td>\n      <td>964</td>\n    </tr>\n    <tr>\n      <th>5</th>\n      <td>55.882</td>\n      <td>4897</td>\n      <td>357</td>\n      <td>2</td>\n      <td>68</td>\n      <td>16</td>\n      <td>Male</td>\n      <td>No</td>\n      <td>Yes</td>\n      <td>Caucasian</td>\n      <td>331</td>\n    </tr>\n  </tbody>\n</table>\n</div>"
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data = pd.read_csv(r'../data/Credit.csv',index_col=0)\n",
    "print(data.shape)\n",
    "data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-09-19T12:11:53.526449Z",
     "start_time": "2023-09-19T12:11:53.511680Z"
    }
   },
   "outputs": [],
   "source": [
    "X = data[['Income','Limit','Rating','Student']]\n",
    "y = data['Balance']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-09-19T12:11:53.559845Z",
     "start_time": "2023-09-19T12:11:53.515508Z"
    }
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/var/folders/vg/w8hv4lqd4h32pw65ggf_yccc0000gn/T/ipykernel_17532/3378374384.py:1: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  X['Student'] = X['Student'].map({'Yes':1,'No':0})\n"
     ]
    },
    {
     "data": {
      "text/plain": "    Income  Limit  Rating  Student\n1   14.891   3606     283        0\n2  106.025   6645     483        1\n3  104.593   7075     514        0\n4  148.924   9504     681        0\n5   55.882   4897     357        0",
      "text/html": "<div>\n<style scoped>\n    .dataframe tbody tr th:only-of-type {\n        vertical-align: middle;\n    }\n\n    .dataframe tbody tr th {\n        vertical-align: top;\n    }\n\n    .dataframe thead th {\n        text-align: right;\n    }\n</style>\n<table border=\"1\" class=\"dataframe\">\n  <thead>\n    <tr style=\"text-align: right;\">\n      <th></th>\n      <th>Income</th>\n      <th>Limit</th>\n      <th>Rating</th>\n      <th>Student</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>1</th>\n      <td>14.891</td>\n      <td>3606</td>\n      <td>283</td>\n      <td>0</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>106.025</td>\n      <td>6645</td>\n      <td>483</td>\n      <td>1</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>104.593</td>\n      <td>7075</td>\n      <td>514</td>\n      <td>0</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>148.924</td>\n      <td>9504</td>\n      <td>681</td>\n      <td>0</td>\n    </tr>\n    <tr>\n      <th>5</th>\n      <td>55.882</td>\n      <td>4897</td>\n      <td>357</td>\n      <td>0</td>\n    </tr>\n  </tbody>\n</table>\n</div>"
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "X['Student'] = X['Student'].map({'Yes':1,'No':0})\n",
    "X.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-09-19T12:11:53.574570Z",
     "start_time": "2023-09-19T12:11:53.525015Z"
    }
   },
   "outputs": [],
   "source": [
    "scaler = StandardScaler()\n",
    "X_scaled = scaler.fit_transform(X)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-09-19T12:11:53.588548Z",
     "start_time": "2023-09-19T12:11:53.525347Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Intercept is  520.015\n",
      "Coef are  [-279.65262476  280.51607343  338.48984662  126.80051361]\n"
     ]
    }
   ],
   "source": [
    "# Linear regression (least square fit)\n",
    "lr = LinearRegression()\n",
    "lr.fit(X_scaled,y)\n",
    "print('Intercept is ',lr.intercept_)\n",
    "print('Coef are ',lr.coef_)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-09-19T12:11:53.590187Z",
     "start_time": "2023-09-19T12:11:53.530588Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Intercept is  520.015\n",
      "Coef are  [-276.1610234   291.29512888  324.17011678  126.4516386 ]\n"
     ]
    }
   ],
   "source": [
    "# Ridge regression \n",
    "ridge = Ridge(alpha = 1)\n",
    "ridge.fit(X_scaled,y)\n",
    "print('Intercept is ',ridge.intercept_)\n",
    "print('Coef are ',ridge.coef_)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-09-19T12:11:53.637455Z",
     "start_time": "2023-09-19T12:11:53.536268Z"
    }
   },
   "outputs": [],
   "source": [
    "# we can see for alpha = 1, we are having almost same value, there is very less effect of regularization"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-09-19T12:11:53.742283Z",
     "start_time": "2023-09-19T12:11:53.538608Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Intercept is  520.015\n",
      "Coef are  [-247.2563987   289.09143853  296.87414298  123.05532307]\n"
     ]
    }
   ],
   "source": [
    "#increasing the values of alpha\n",
    "ridge = Ridge(alpha = 10)\n",
    "ridge.fit(X_scaled,y)\n",
    "print('Intercept is ',ridge.intercept_)\n",
    "print('Coef are ',ridge.coef_)\n",
    "# see the values decreasing, and moving towards zero"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-09-19T12:11:53.742899Z",
     "start_time": "2023-09-19T12:11:53.541938Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Intercept is  520.015\n",
      "Coef are  [0.83828411 1.56753041 1.57106622 0.47383595]\n"
     ]
    }
   ],
   "source": [
    "# Large value of alpha\n",
    "ridge = Ridge(alpha = 100000)\n",
    "ridge.fit(X_scaled,y)\n",
    "print('Intercept is ',ridge.intercept_)\n",
    "print('Coef are ',ridge.coef_)\n",
    "# all the values are pretty much close to 0 now. "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "https://seaborn.pydata.org/generated/seaborn.lineplot.html"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-09-19T12:11:53.752123Z",
     "start_time": "2023-09-19T12:11:53.545017Z"
    }
   },
   "outputs": [],
   "source": [
    "alpha = [1e-1,1e1,1e2,1e5,1e7,1e9]\n",
    "intercept_dict = {}\n",
    "\n",
    "for a in alpha:\n",
    "    ridge = Ridge(alpha = a)\n",
    "    ridge.fit(X_scaled,y)\n",
    "    intercept_dict[a] = list(ridge.coef_)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-09-19T12:11:53.752869Z",
     "start_time": "2023-09-19T12:11:53.551896Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": "                       0           1           2           3\n1.000000e-01 -279.302308  282.432925  336.217625  126.768867\n1.000000e+01 -247.256399  289.091439  296.874143  123.055323\n1.000000e+02  -98.926545  210.494675  212.169527   98.060125\n1.000000e+05    0.838284    1.567530    1.571066    0.473836\n1.000000e+07    0.008515    0.015826    0.015861    0.004757\n1.000000e+09    0.000085    0.000158    0.000159    0.000048",
      "text/html": "<div>\n<style scoped>\n    .dataframe tbody tr th:only-of-type {\n        vertical-align: middle;\n    }\n\n    .dataframe tbody tr th {\n        vertical-align: top;\n    }\n\n    .dataframe thead th {\n        text-align: right;\n    }\n</style>\n<table border=\"1\" class=\"dataframe\">\n  <thead>\n    <tr style=\"text-align: right;\">\n      <th></th>\n      <th>0</th>\n      <th>1</th>\n      <th>2</th>\n      <th>3</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>1.000000e-01</th>\n      <td>-279.302308</td>\n      <td>282.432925</td>\n      <td>336.217625</td>\n      <td>126.768867</td>\n    </tr>\n    <tr>\n      <th>1.000000e+01</th>\n      <td>-247.256399</td>\n      <td>289.091439</td>\n      <td>296.874143</td>\n      <td>123.055323</td>\n    </tr>\n    <tr>\n      <th>1.000000e+02</th>\n      <td>-98.926545</td>\n      <td>210.494675</td>\n      <td>212.169527</td>\n      <td>98.060125</td>\n    </tr>\n    <tr>\n      <th>1.000000e+05</th>\n      <td>0.838284</td>\n      <td>1.567530</td>\n      <td>1.571066</td>\n      <td>0.473836</td>\n    </tr>\n    <tr>\n      <th>1.000000e+07</th>\n      <td>0.008515</td>\n      <td>0.015826</td>\n      <td>0.015861</td>\n      <td>0.004757</td>\n    </tr>\n    <tr>\n      <th>1.000000e+09</th>\n      <td>0.000085</td>\n      <td>0.000158</td>\n      <td>0.000159</td>\n      <td>0.000048</td>\n    </tr>\n  </tbody>\n</table>\n</div>"
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tmp = pd.DataFrame(intercept_dict).T\n",
    "tmp.index = alpha\n",
    "tmp"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-09-19T12:12:18.779069Z",
     "start_time": "2023-09-19T12:12:18.604154Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": "Text(0.5, 0, 'Alpha')"
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "text/plain": "<Figure size 1600x800 with 1 Axes>",
      "image/png": "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"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize = (16,8))\n",
    "sns.lineplot(data = tmp)\n",
    "plt.axhline(y = 0,linestyle = 'dashed',lw = 0.1,color = 'black')\n",
    "plt.xticks(alpha)\n",
    "plt.xlim(0,10)\n",
    "plt.ylabel('Coeffients')\n",
    "plt.xlabel('Alpha')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-09-19T12:11:54.397274Z",
     "start_time": "2023-09-19T12:11:53.901087Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": "Text(0.5, 0, 'Alpha')"
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "text/plain": "<Figure size 1600x800 with 1 Axes>",
      "image/png": "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"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# using log scale for x axis\n",
    "\n",
    "plt.figure(figsize = (16,8))\n",
    "sns.lineplot(data = tmp)\n",
    "plt.axhline(y = 0,linestyle = 'dashed',lw = 0.1,color = 'black')\n",
    "plt.xticks(alpha)\n",
    "plt.xscale('log')\n",
    "plt.ylabel('Coeffients')\n",
    "plt.xlabel('Alpha')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-09-19T12:11:54.397584Z",
     "start_time": "2023-09-19T12:11:54.121055Z"
    }
   },
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
